Prompt Engineering for Philosophy & Religion
LLMs have made philosophy and religious studies unexpectedly practical: the same models that raise the sharpest ethical questions also give scholars new tools to read, compare, and interrogate canonical texts. This is a field where careful prompting and domain knowledge matter more than raw compute.
Where this is showing up in Philosophy & Religion
- The NIST AI Risk Management Framework (AI RMF 1.0, Jan 2023) and its Generative AI Profile (NIST-AI-600-1, July 2024) define the trustworthiness criteria — fairness, accountability, explainability — that now shape corporate and government AI ethics review.
- PhilPapers (204K+ entries) maintains an active Large Language Models bibliography, and philosophers like Himmelreich and Meyer have released PhilLit, a Claude-backed literature-review assistant purpose-built for the discipline.
- In religious studies, Yale Divinity Library's Computational Theology Lab (established 2025), Iliff School's Theologies of the Digital project, and open datasets like Open Scripture Intelligence are treating canonical texts as structured knowledge bases for semantic search and cross-reference work.
- The OECD AI Principles, the EU AI Act, and ongoing alignment research at Anthropic and OpenAI are driving a steady stream of primary-source material for applied-ethics courses.
Projects you could build in this course
- A dialogue agent grounded in a philosophical tradition (e.g., Stoic, Thomist, utilitarian) that cites primary texts
- A RAG assistant over a canonical corpus — the Platonic dialogues, the Pauline epistles, the Analects
- An argument-structure and fallacy-analysis tool benchmarked against NIST AI RMF trustworthiness criteria